Tiny summary but detailed notes for each. Use the ISBN number to find it from your local library or anywhere else. This page will constantly update as I read more, so bookmark it if you want to check back in a few months.

Sorted with my top recommendations up top. Sort by title, newest, or best.

This free, online course is for someone who wants to start doing data science and machine learning right now. You’ll spend more time writing code than reading about it. You’ll get the theoretical background you need to make good modeling decision, but won’t waste your time with historical background that won’t help you become a practicing data scientist.

By Quinn Slack on January 9, 2018
Sourcegraph Server 2.4 is here. It is now free for unlimited users and repositories, can be installed in minutes with a single docker run command, and is easily configurable in the new web-based site admin. This release also includes many performance and bug fixes, plus a better interface for monitoring search results.

Sourcegraph Server gives the power of great code search to every developer at your company, so you can ship better code faster. It runs securely in your own network, takes 5 minutes to install, and is easy to upgrade.

The notion that Homeric epic must be rendered in grand, ornate, rhetorically elevated English has been with us since the time of Alexander Pope. It is past time, I believe, to reject this assumption. Homer's language is markedly rhythmical, but it is not difficult or ostentatious, The Odyssey relies on coordinated, not subordinated syntax ("and then this, and then this, and then this," rather than "although this, because of that, when this, which was this, on account of that")

The microphone in an iPhone or Apple Watch turns your voice into a stream of instantaneous waveform samples, at a rate of 16000 per second. A spectrum analysis stage converts the waveform sample stream to a sequence of frames, each describing the sound spectrum of approximately 0.01 sec. About twenty of these frames at a time (0.2 sec of audio) are fed to the acoustic model, a Deep Neural Network (DNN) which converts each of these acoustic patterns into a probability distribution over a set of speech sound classes: those used in the “Hey Siri” phrase, plus silence and other speech, for a total of about 20 sound classes. See Figure 2.
The DNN consists mostly of matrix multiplications and logistic nonlinearities. Each “hidden” layer is an intermediate representation discovered by the DNN during its training to convert the filter bank inputs to sound classes. The final nonlinearity is essentially a Softmax function (a.k.a. a general logistic or normalized exponential), but since we want log probabilities the actual math is somewhat simpler.

Here’s a popular story about momentum [1, 2, 3]: gradient descent is a man walking down a hill. He follows the steepest path downwards, his progress is slow, but steady. Momentum is a heavy ball rolling down the same hill. The added inertia acts both as a smoother and an accelerator, dampening oscillations and causing us to barrel through narrow valleys, small humps and local minima.

This standard story isn’t wrong, but it fails to explain many important behaviors of momentum. In fact, momentum can be understood far more precisely if we study it on the right model.

One nice model is the convex quadratic. This model is rich enough to reproduce momentum’s local dynamics in real problems, and yet simple enough to be understood in closed form. This balance gives us powerful traction for understanding this algorithm.

The web is a powerful medium to share new ways of thinking. Over the last few years we’ve seen many imaginative examples of such work. But traditional academic publishing remains focused on the PDF, which prevents this sort of communication.

Seeing Theory is a project designed and created by Daniel Kunin with support from Brown University's Royce Fellowship Program and National Science Foundation group STATS4STEM. The goal of the project is to make statistics more accessible to a wider range of students through interactive visualizations.

Statistics, is quickly becoming the most important and multi-disciplinary field of mathematics. According to the American Statistical Association, statistician is one of the top ten fastest-growing occupations and statistics is one of the fastest-growing bachelor degrees. Statistical literacy is essential to our data driven society. Yet, for all the increased importance and demand for statistical competence, the pedagogical approaches in statistics have barely changed. Using Mike Bostock’s data visualization software, D3.js, Seeing Theory visualizes the fundamental concepts covered in an introductory college statistics or Advanced Placement statistics class. Students are encouraged to use Seeing Theory as an additional resource to their textbook, professor and peers.

In this article we will analyze a dataset from the California Department of Water Resources (CDWR) looking at the several vital statistics for the Oroville dam. This article provides realtime analysis with Chart Lab graphs (updated hourly and automatically with data taken from the CDWR website), which show the current situation at the dam. Additionally, this article illustrates how publicly available data from the California DWR can be easily loaded into the non-relational Axibase Time Series Database (ATSD) for interactive analysis with graphical representation of open data published by government organizations.

This is a guide that anyone could use to learn about the practice of front-end development. It broadly outlines and discusses the practice of front-end engineering: how to learn it and what tools are used when practicing it in 2017.

Chemists can calculate the energy or length of any chemical bond, but it has never been explained in the context of quantum mechanics. The very concept of a chemical bond, while immeasurably useful, is a seductive abstraction, Charles Coulson observed:

> Sometimes it appears to me that a bond between two atoms has become so real, so tangible, so familiar that I can almost see it. But then I awake with a little shock: for the chemical bond is not a real thing, it does not exist, and no one has ever seen or will ever see it. It is a figment of our imagination.19

Glance is a visual syntax for the programming language Haskell. The goal of this project is to increase programmer happiness and productivity by allowing programmers to create and understand programs in new and different ways. Currently, the Glance executable produces a visual representation of your code in the form of an SVG image when given a textual Haskell source file. In the future, I hope to create a visual editor for Haskell. Please scroll down to see some example images.

Have you ever wondered what really goes on when your computer takes a higher-level language, like Javascript or C, and turns it into something it can read? Quine8 (Q8) is a simple virtual machine that takes the most basic building block a computer can operate on, bytecode and runs it at a fraction of the speed of a real CPU, allowing you to watch it run each step of the way.

Laboratory research shows that by asking why did it fail rather than why might it fail, gets the creative juices flowing. (The same principle can work in finding solutions to tough problems. Assume the problem has been solved, and then ask, how did it happen? Try it!)

We use the John F. Canny technique for finding edges. It is a multi-step process as follows:

Apply the Sobel kernel to the smoothed image from the above step
The Sobel kernel has two parameters:
min threshold
max threshold
The Sobel kernel uses the min, max to identify an area of a high contrast surrounded by a low contrast
The solid white line above is a good example:
Area of low contrast around the white line (high contrast) help to define an edge or more accuratly a line segment
Finally a good contrast ratio between min:max is 1:3